Prescription pattern of non-steroidal anti-inflammatory drugs and their effects on symptoms and disease progression in patients with osteoarthritis in tertiary care centre
Bibliographic record
Abstract
Objective: Purpose of this study is to evaluate prescribing pattern of NSAIDS in osteoarthritis patients and their effect on symptoms and disease progressionMaterials and Methods: The Prospective observational study was performed on 200 study participants of both sexes from orthopaedic Out Patient Department (OPD) from a tertiary care hospital, Prakash Institute of medical science in Kolhapur between span of Aug 2019 to Aug 2020 who were diagnosed with Osteoarthritis and prescribed with NSAIDS for a minimum period of 3 months. After the period of treatment improvement in symptom was assessed by Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scale to evaluate specific symptoms in subsequent visit at interval of 1 month for 3 follow ups.Results: Most common NSAIDs prescribed in orthopaedic OPD patients were diclofenac (51%), Paracetamol (50.5%), Aceclofenac (43%), Tramadol (15%), Ibuprofen (7%), etoricoxib (6%), Naproxen (5%). Paracetamol was most frequently prescribed as combination therapy along with diclofenac, Tramadol and aceclofenac, and diclofenac was commonly used as monotherapy. Tramadol combined with paracetamol has been used in only 22 patients (13%) in the present study. Changes in pain, stiffness and physical function subscale after 3 months follow up were significant compare to initial visit in WOMAC score.Conclusion: Non-steroidal anti-inflammatory drugs are most commonly used drug for the management of pain and inflammation. From our study it was observed that conventional type of NSAIDS are used most common. NSAIDs are vital for clinical management of OA and to improve quality of life. Aceclofenac with paracetamol combination therapy and Diclofenac monotherapy were most frequently prescribed among the NSAIDs. Safety is the proven concern in treating chronic conditions in OA, hence Aceclofenac and Paracetamol is recommended as combination therapy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".